Untitled

Abstract

In drug design, often enough, no structural information on a particular receptor protein is available. However, frequently a considerable number of different ligands is known together with their measured binding affinities towards a receptor under consideration. In such a situation, a set of plausible relative superpositions of different ligands, hopefully approximating their putative binding geometry, is usually the method of choice for preparing data for the subsequent application of 3D methods that analyze the similarity or diversity of the ligands. Examples are 3D-QSAR studies, pharmacophore elucidation, and receptor modeling. An aggravating fact is that ligands are usually quite flexible and a rigorous analysis has to incorporate molecular flexibility. We review the past six years of scientific publishing on molecular superposition. Our focus lies on automatic procedures to be performed on arbitrary molecular structures. Methodical aspects are our main concern here. Accordingly, plain application studies with few methodical elements are omitted in this presentation. While this review cannot mention every contribution to this actively developing field, we intend to provide pointers to the recent literature providing important contributions to computational methods for the structural alignment of molecules. Finally we provide a perspective on how superposition methods can effectively be used for the purpose of virtual database screening. In our opinion it is the ultimate goal to detect analogues in structure databases of nontrivial size in order to narrow down the search space for subsequent experiments.

2D QSAR studies on a series of bifonazole derivatives with antifungal activity

“…: comparative molecular field analysis -CoMFA) and 3D pharmacophore models, as these methods are highly dependent on molecular alignment. 13 Alternatively, we resorted to 2D QSAR approaches that require no explicit 3D information for the ligands (e.g. putative binding conformations and molecular alignment), employing both classical and fragment-based hologram QSAR (HQSAR) methods.…”

Predicting Molecular Interactions in silico: I. A Guide to Pharmacophore Identification and its Applications to Drug Design

“…An example for a method that ensures conformational diversity is the poling technique, which penalizes a newly generated conformation if it is too close to an already existing one [30]. 8 …”

“…Methods that represent the structure of the molecule by using continuous properties such as molecular shapes, lattices or molecular fields [5][6][7][8] are beyond the scope of this review.…”

Metrics for measuring distances in configuration spaces

“…Diversity analysis is at the heart of any structure prediction method in material science and solid state physics [1][2][3][4][5] and conformer search in structural biology and drug discovery. [6][7][8][9][10][11][12] In the latter case, most of the proposed approaches [13][14][15] use approximate methods that reduce the structure description information, e.g. by excluding the side chains in a protein or a two dimensional representations of the molecule, [16] to speed up the searching procedure.…”